Zuckerberg Muse Wonder investment bet
Mark Zuckerberg just admitted that betting $100 billion to $200 billion on Meta's first frontier model, Muse Wonder, felt like entrepreneurship on hard mode rather than a lean startup approach. He questioned Alexandr Wang directly about whether the investment would actually work despite feeling good about the progress, and Wang confirmed it was certainly not clear at all that success was guaranteed. The strategy requires pushing all chips in before dealing the cards because waiting to see if models work leaves you radically behind. Internal tests reportedly rank Muse Wonder alongside Fable 5.1 and GPT-6 Astra on MemoryBench while outperforming Fable, Opus, and Astra according to Meta's own data. Pricing is set at $4 input and $20 output per million tokens, matching the tier of Opus 5.5. This beast of a model was trained at Prometheus, a new Meta data center located in Ohio, though no independent benchmarks have been released yet.
Transcript (en)
Okay, we're talking about models a lot. Tell me about the new model. It sounds awesome. Yeah, I mean, I think we're quite proud of this. Yeah, the new model, Muse Wonder, it's a new class of model that is at the frontier. I think this is, this is like, you know, in some sense, it's like entrepreneurship on hard mode. It's like the opposite of lean startup. Like lean startup is like, yeah, you like, see if you get something working, and then you double down, and then you see if that works, then you double down. Like, you cannot do that in AI. You have to, like, we've, I mean, we've been investing into these data centers since, you know, for years and years and years. We've had to. And you'll be radically behind if you wait to see if things are working. So we have these conversations where it's like, at the end of last year, we're like, all right, we are quite excited about the progress. We haven't seen the models yet. Like, it's like, I'm going to like, you know, we're going to write this check for like, I don't know, like $100 billion or $200 billion. I'm like, Alex, are you sure this is going to work? I mean, I was feeling good about it, but it was certainly not clear at all that it was going to work. You guys are saying that the essence of training a Frontier model is you have to push your chips all in before you've been dealt the cards. Yes.
